Probabilities of Rainfall-Induced Landslides in Climate Change Scenarios

Climate change is expected to impact future occurrences of shallow, rainfall induced, landslides, mainly due to modification in the meteorological forcings. Quantification of expected changes in landslide frequency is a key step for properly designing adaptation strategies, although few papers address this issue in current literature.

In this work, a modeling framework for assessing the impacts of climate change on landslide probability and return period that capitalizes on the combined use of a stochastic rainfall model, RCM simulations, and a hydrological and slope stability model is presented. The combined models enable to estimate landslide probability through Monte Carlo simulations. Climate change is then introduced by perturbing the parameters of the rainfall stochastic generator based on factors of change derived from the comparison of future scenarios and the baseline climate as simulated by Regional climate models (RCMs). By applying sequentially the modeling chain on a future moving time window, a yearly series of future landslide triggering probabilities can be estimated, and landslide return periods can be also computed making use of expressions able to take into account the underlying non stationarity.

The developed methodology is applied to the landslide prone region of Peloritani Mountains, Southern Italy, making use of climate change projections of several RCMs of the CORDEX initiative. An assessment of the impacts of intermediate- and high-emission scenarios, RCP 4.5 and RCP 8.5, indicates that many RCMs predict, for both scenarios, a significant modification of landslide hazard in the future.